Échantillonnés

Échantillonnés is a French term that translates to "sampled" in English. It is commonly used in various fields, particularly in statistics, data analysis, and scientific research, to describe a process where a subset of a larger group or population is selected for examination or measurement. The goal of sampling is typically to gain insights into the characteristics of the entire population without having to study every individual or element within it.

In statistics, "échantillonnés" refers to the data points or observations collected from a sample. This sample is chosen to be representative of the population from which it was drawn, allowing researchers to make inferences and draw conclusions about the population. Various sampling techniques exist, such as random sampling, stratified sampling, and cluster sampling, each with its own advantages and suitability for different research objectives.

In digital signal processing, "échantillonnés" describes the process of converting a continuous-time analog signal into a discrete-time digital signal. This involves taking measurements of the signal's amplitude at regular intervals. The frequency at which these measurements are taken is known as the sampling rate, and it plays a crucial role in determining the fidelity of the digital representation of the original analog signal. The Nyquist-Shannon sampling theorem is a fundamental principle in this domain, outlining the minimum sampling rate required to perfectly reconstruct the original signal.

The concept of "échantillonnés" is also relevant in fields like market research, where a sample of consumers might be surveyed to understand broader market trends, or in quality control, where a sample of manufactured goods might be inspected to assess the overall quality of a production batch. The principle remains consistent: studying a part to understand the whole.